Package: DRsurvCRT Type: Package Title: Doubly-Robust Estimation for Survival Outcomes in Cluster-Randomized Trials Version: 0.0.1 Authors@R: c( person(given = "Xi", family = "Fang", role = c("aut","cre"),email = "x.fang@yale.edu"), person(given = "Fan", family = "Li", role = c("aut"), email = "fan.li@example.edu") ) Description: Cluster-randomized trials (CRTs) assign treatment to groups rather than individuals, so valid analyses must distinguish cluster-level and individual-level effects and define estimands within a potential-outcomes framework. This package supports right-censored survival outcomes for both single-state (binary) and multi-state settings. For single-state outcomes, it provides estimands based on stage-specific survival contrasts (SPCE) and restricted mean survival time (RMST). For multi-state outcomes, it provides SPCE as well as a generalized win-based restricted mean time-in-favor estimand (RMT-IF). The package implements doubly robust estimators that accommodate covariate-dependent censoring and remain consistent if either the outcome model or the censoring model is correctly specified. Users can choose marginal Cox or gamma-frailty Cox working models for nuisance estimation, and inference is supported via leave-one-cluster-out jackknife variance and confidence interval estimation. Methods are described in Fang et al. (2025) "Estimands and doubly robust estimation for cluster-randomized trials with survival outcomes" . License: MIT + file LICENSE Encoding: UTF-8 LazyData: true Imports: Rcpp, frailtyEM, survival, ggplot2, pracma, abind LinkingTo: Rcpp, RcppArmadillo RoxygenNote: 7.3.3 Depends: R (>= 3.5) NeedsCompilation: yes Packaged: 2026-07-14 05:39:27 UTC; root Author: Xi Fang [aut, cre], Fan Li [aut] Maintainer: Xi Fang Repository: https://cran.r-universe.dev Date/Publication: 2025-12-30 19:00:06 UTC RemoteUrl: https://github.com/cran/DRsurvCRT RemoteRef: HEAD RemoteSha: aa436d0f01cfb0ec59176851622a10bb802bf323